6.1 The Standard Normal Distribution 1. Fill in the blanks using both our textbook and Lumen textbook. 2. A normal distribution is a continuous probability density function used to model the probability distribution of a random variable. The functions of all normal distributions are already defined: f(x) = So, every normal distribution is completely determined by the two parameters . and ., which are called the mean and the standard deviation. 3. If X ~ N(3, 1), then P(X = 4) = 0 and P(X < 4) = P(X < 4) because every normal distribution function is a probability density function of a continuous random variable. 4. When X ~ N(µ,0), a probability P(a < X < b) is given as the area between the graph and the x-axis over [a,b]. 5. One way of using normal distribution modeling: For a random variable whose mean and standard deviation are known, we assume that the random variable fits the normal distribution with the same mean and standard deviation. Then, we use the normal distribution to find the probabilities of the variable. 6. Notation. X ~ N(µ,0) means that

6.1 The Standard Normal Distribution 1. Fill in the blanks using both our textbook and Lumen textbook. 2. A normal distribution is a continuous probability density function used to model the probability distribution of a random variable. The functions of all normal distributions are already defined: f(x) = So, every normal distribution is completely determined by the two parameters . and ., which are called the mean and the standard deviation. 3. If X ~ N(3, 1), then P(X = 4) = 0 and P(X < 4) = P(X < 4) because every normal distribution function is a probability density function of a continuous random variable. 4. When X ~ N(µ,0), a probability P(a < X < b) is given as the area between the graph and the x-axis over [a,b]. 5. One way of using normal distribution modeling: For a random variable whose mean and standard deviation are known, we assume that the random variable fits the normal distribution with the same mean and standard deviation. Then, we use the normal distribution to find the probabilities of the variable. 6. Notation. X ~ N(µ,0) means that

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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